This week I was speaking at e-Commerce Unpacked conference in Dublin – just in time for Black Friday! During the session I discussed the key differences in GA4 vs Universal Analytics, why a considered move to GA4 is important and some tips on how eCommerce businesses can use reports available to derive customer insight.
Below is a list of some of the main points discussed:
1. Start planning your migration to GA4 now if you haven’t considered this already
- Google Analytics 4 is the next generation of Google Analytics.
- GA4 has been built to provide a more holistic and insight-driven analytics platform, one that is more suited to evolving privacy regulations and considerations.
- Universal Analytics will sunset from July 2023 (July 2024 for 360 customers), meaning a moveto GA4 is a requirement.
- After that, you’ll be able to access your previously processed data in Universal Analytics for at least six months.
2. Consider how you are going to keep your Universal Analytics data
- If you are a 360 (enterprise) customer you can take advantage of the connection to BigQuery and export data to your BigQuery project.
- If you aren’t a 360 customer you can export UA data into multiple formats including CSV, Excel, PDF and Google Sheets.
- There is also a Google Analytics Reporting API that you can connect to export data.
3. Consider if you are going to use the blended or observed data option for your reporting identity
In short, reporting identity can be split into Observed, Blended or Device based.
Depending on which option you choose, Google will sequentially go through the sub options available to identify the user visiting your site. The new option available with GA4 is modelling (under the blended identity option) which will allow you to enhance reports with additional data for users who have decided to decline primary analytics IDs e.g. cookies. In this case, Google Analytics uses data of similar users to fill the gap.
Blended: Identity by User-ID, Google signals, device ID, then modelling. Uses the User-ID if it is collected. If no User-ID is collected, then Analytics uses information from Google signals if that is available. If neither User-ID nor Google signals information is available, then Analytics uses the device ID. If no identifier is available, Analytics uses modelling.
Observed: Identity by User-ID, Google signals, then device ID. Uses the User-ID if it is collected. If no User-ID is collected, then Analytics uses information from Google signals if that is available. If neither User-ID nor Google signals information is available, then Analytics uses the device ID.
Device based: Uses only the device ID and ignores all other IDs that are collected.
4. Understand that with Universal vs GA4 data you aren’t always comparing apples with apples
There’s a full list of comparable/non-comparable stats here but some differences include:
• Total Users is available in UA and GA4
• Active Users only available in GA4 and used as the primary metric- number of users that have been active in a 28 day period
• In UA a session is the time a user is engaged with your website but ends after new campaign parameters, 30 minutes of inactivity, midnight or tab close.
• In GA4 an event generates a session and ends after 30 minutes of inactivity but does not start at midnight or end with new campaign parameters.
• 5 goal types available in UA (destination, duration, page/session, smart goal and event goals)
• Conversion events only available in GA4.
• Some goals e.g. duration goal is not possible to duplicate in GA4.
• UA counts one conversion per session, GA4 counts multiple conversions per session.
Check out Krista Seiden’s Looker report tracking the differences in UA vs GA4 data
5. UTM tag every link you send out as part of a marketing campaign
Correct categorisation of inbound traffic to your site is vital. Don’t leave this up to Google or to chance by not taking the time to decorate links.
Taking time to run URLs through the URL builder means you’ll be able to control and tie the source, medium, campaign name and channel group back to traffic that clicks on a link that you’ve used as part of your marketing campaign.
Using the Google Campaign URL Builder is the easiest and cheapest way to create custom UTM Links.
Simply fill in all the fields and it will auto-generate the UTM link for you – you can then copy and paste this into your social media post/email etc.
Check out our previous blog on how to campaign tag using UTMs for more details. This means, when you check Google Analytics, most of your campaigns should be correctly categorised into the right channel/source/medium:
*NOTE that manual tagging doesn’t need to be used for accounts that can be natively connected to GA4 e.g. Google Ads.
6. Link your ads account
Linking your Google Ads account will allow you to not only track traffic directly from Google Ads through to Analytics but will also allow you to use Audiences that you’ve built in GA4 as targeted audiences in Google Ads, meaning you can target or create similar-to lists of audiences that you’d like to remarket to via Google Ads campaigns:
7. Take advantage of all the audiences available
One of the advantages of moving to GA4 is being able to use the predictive and machine learning elements of the product.
This includes being able to use the Predictive Lifetime Value metric and auto-created predictive audiences including:
- Likely seven-day purchasers
- Predicted 28 day top spenders
- Likely first-time seven-day purchasers
8. Use The Conversion Path report
Conversion paths reports can be used to understand your customers’ paths to conversion, meaning you are no longer focused on last-click paths but understanding how different channels need to work in conjunction with each other to drive ultimate value. In Universal Analytics, these reports were called Multi-Channel Funnel reports, in GA4 they are Conversion Path reports:
9. Use the Attribution reports
Google Analytics 3 used a last click attribution model across all channels, excluding direct. Conversions and ecommerce transactions are credited to the last non-direct campaigns, search or ad that directed the user to the site when they converted.
Google Analytics 4 uses a model called Data Driven Attribution- Data Driven Attribution uses machine learning algorithms to evaluate both converting and non-converting paths. The resulting Data-driven model learns how different touchpoints impact conversion outcomes.
You can, however, use the Model comparison tool to understand how, when multiple models are applied, change the value of each channel:
10. Use the Exploration report for funnel analysis
An important user interface update in GA4 is the reduced number of pre-built reports compared to Universal Analytics. This is because GA4 makes use of a new reporting feature called Explorations.
GA4 does not yet have eCommerce funnels built into the out-of-the-box reports, however, you can access eCommerce funnel reports using the Exploration reports:
Check out the range of pre-built reports, including those that relate to funnel and eComm analysis in GA4’s template gallery.
Our team of Google Analytics Specialists are helping clients migrate to GA4 in a smooth and considered way and working with eCommerce clients to power digital campaigns with data-powered insights and targeting. If you are interested in hearing more about what we can do, get in touch with us today!